criterion module¶

Acquisition criterion for which the optimum would improve the regression model.

An acquisition criterion (also called infill criterion) is a function taking a model input value and returning a value of interest to maximize (default option) or minimize according to the meaning of the acquisition criterion.

Then, the input value optimizing this criterion can be used to enrich the dataset used by a machine learning algorithm in its training stage. This is the purpose of adaptive learning.

This notion of acquisition criterion is implemented through the MLDataAcquisitionCriterion class which is built from a MLSupervisedAlgo and inherits from MDOFunction.

class gemseo_mlearning.adaptive.criterion.MLDataAcquisitionCriterion(algo_distribution, **options)[source]

Bases: MDOFunction

Acquisition criterion.

# noqa: D205 D212 D415

Parameters:

algo_distribution (MLRegressorDistribution) – The distribution of a machine learning algorithm.
**options (MLDataAcquisitionCriterionOptionType) – The acquisition criterion options.

MAXIMIZE: ClassVar[bool] = True

algo_distribution: MLRegressorDistribution: The distribution of a machine learning algorithm assessor.

force_real: bool: Whether to cast the results to real value.

has_default_name: bool: Whether the name has been set with a default value.

last_eval: OutputType | None

The value of the function output at the last evaluation.

None if it has not yet been evaluated.

output_range: float: The output range.

special_repr: str: The string representation of the function overloading its default string ones.

class gemseo_mlearning.adaptive.criterion.MLDataAcquisitionCriterionFactory[source]

Bases: BaseFactory

A factory of MLDataAcquisitionCriterion.

Return type:: BaseFactory

property available_criteria: list[str]: The names of the available criteria.

failed_imports: dict[str, str]: The class names bound to the import errors.